Comparison of thresholding algorithms for automatic overhead line detection procedure

• Autorzy: Kowalski, Paweł , Smyka, Robert
• Języki publikacji: EN

Abstrakty

EN

The article presents an overview of the thresholding algorithms. It compares the algorithms proposed by Pun, Kittler, Niblack, Huang, Rosenfeld, Remesh, Lloyd, Riddler, Otsu, Yanni, Kapur and Jawahar. Additionally, it was tested how the tuning of the Pun, Jawahar and Niblack methods affects the thresholding efficiency and proposed a combination of the Pun algorithm with a priori algorithm. All presented algorithms have been implemented and tested for effectiveness in detecting overhead lines.

PL

W artykule przedstawiono przegląd algorytmów progowania. Porównano w nim algorytmy zaproponowane przez Puna, Kittlera, Niblacka, Huanga, Rosenfelda, Remesha, Lloydaa, Riddlera, Otsu, Yanni, Kapura i Jawahara. Dodatkowo przetestowano, jak dostrajanie metod Puna, Jawahara i Niblacka wpływa na skuteczność progowania oraz zaproponowano połączenie algorytmu Puna z algorytmem a priori. Wszystkie przedstawione algorytmy zostały zaimplementowane i przetestowane pod kątem skuteczności w wykrywaniu linii napowietrznych

Słowa kluczowe

PL

progowanie; linia elektroenergetyczna; przetwarzanie obrazu

EN

thresholding; power line; image processing

• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2022
• Tom: R. 98, nr 3
• Strony: 149--155
• Opis fizyczny: Bibliogr. 24 poz., rys.

Twórcy

autor

Kowalski, Paweł

• Department of Electrical and High Voltage Engineering, Faculty of Electrical and Control Engineering, Gdańsk University of Technology, ul. Gabriela Narutowicza 11/12 80- 233 Gdańsk, Poland,

autor

Smyka, Robert

• Department of Electrical and High Voltage Engineering, Faculty of Electrical and Control Engineering, Gdańsk University of Technology, ul. Gabriela Narutowicza 11/12 80- 233 Gdańsk, Poland,

Bibliografia

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• [4] P. Kowalski, Application of image processing methods for over- head power lines monitoring. PhD thesis, Gdansk University of Technology, 2020. (in Polish).
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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).

Identyfikatory

DOI

10.15199/48.2022.03.34